MOOCs Types and Course Development

Zarema S. Seidametova

1 a

Crimean Engineering and Pedagogical University, 8 Uchebnyi Ln., Simferopol, 95015, Ukraine

Keywords:

Massive Open Online Courses, cMOOC, xMOOC, Quasi MOOC, MOOCs Video Design, Online Course,

E-Learning.

Abstract:

Massive open online courses (MOOCs) are the new additional dimension of education that allow to study

online courses from different universities geographically located anywhere around the world. We consider the

MOOCs classiﬁcation based on pedagogical approaches and product functionalities (cMOOC, xMOOC, quasi

MOOC). We present diagrams of the planning, prior preparation and the development of the MOOC. There

are four stages of the process: preproduction, production, postproduction and maintenance. We present the

typical roadmap of MOOC development: guidelines to develop course content, video content implementation,

and development of roles. We introduce as example the video content matrix of the quasi-MOOC “Unity

Augmented Reality for Beginners”. We recommend the following roles for the MOOC development team:

experts, curriculum designers and technical specialists. This set of roles needs for effective design of MOOC.

1 INTRODUCTION

The educational community has begun to use since

2008 the term – massive open online courses

(MOOCs) to denote a certain format of open online

courses. According a study (Shah, 2020b) conducted

by the MOOC Class Central by the end of 2020 the

size of the modern “MOOC movement” reached more

than 950 universities, more than 180 million students

(excluding China); the number of MOOC courses are

more than 16,300. According (Shah, 2020a), one

third of the learners that ever registered on a MOOC

platform joined in 2020. The pandemic brought many

people into online education. MOOC providers, in

particular, attracted many learners with free online

courses from top universities.

The largest provider of online courses Coursera

(https://www.coursera.org) has expanded its audience

to 76 million learners, edX (https://www.edx.org) –

35 million. Duolingo (https://www.duolingo.com), a

popular language platform, has more than 300 mil-

lion users (they do not receive formal certiﬁcation, in

contrast to the previously mentioned 180 million uni-

versity students).

The top MOOC providers (Coursera, edX, and Fu-

tureLearn) registered as many new learners in April

2020 as in the whole 2019 year. Around 25–30% of

their total registered users on these MOOC platforms

https://orcid.org/0000-0001-7643-6386

came after the pandemic. Coursera added the largest

number of new learners (more than 35 million enroll-

ments between March 2020 and July 2020).

Online learning helps students to improve their

performance. Different online learning environments

(OLE) have their own way of systems implementa-

tion. Technological developments made it a lot easier

to develop and customized learning solutions that are

focused on adaptive and personalized e-learning en-

vironments. OLE platforms can be adapted by higher

institutions to enhance teaching and learning process.

MOOC provides quality to e-learning from experts

without almost no costs.

Despite the growing number of educators who

have started to develop the MOOC courses, the design

of the MOOC is not simple. Educators (developers of

the MOOC) should be familiar not only with peda-

gogical approaches, but also with logistical, techno-

logical and ﬁnancial issues. They need to plan care-

fully the feasibility of the course depending on the

available resources. The authors of the paper (Alario-

Hoyos et al., 2014) propose the conceptual environ-

ment “MOOC Canvas” to support teachers in the de-

scription and design of the MOOCs.

The desire of educational institutions to improve

the quality of education leads to the need to increase

the cost of the development and maintenance for edu-

cational services, and, consequently, the ﬁnal cost of

training increases. In the economic scale, the MOOCs

560

Seidametova, Z.

MOOCs Types and Course Development.

DOI: 10.5220/0011009400003364

In Proceedings of the 1st Symposium on Advances in Educational Technology (AET 2020) - Volume 2, pages 560-568

ISBN: 978-989-758-558-6

model reduces the cost of learning per student. For

example, if $300,000 were spent on the development

of one MOOC with an audience of 100,000 students,

then we got about $3 per student (Saltzman, 2014,

2017). MOOC companies need to cover the startup

costs and ﬁnancing activities. For example, Coursera

in November 2013 attracted $85 million of venture

capital, including funding from partner universities,

the World Bank and venture capital companies. MIT

and Harvard University allotted $30 million each, cre-

ating EdX.

The original concept of the MOOC assumed that

MOOCs are free courses with open access for a huge

number of learners from all over the world. In recent

years a large number of researchers have discussed

the development of MOOCs in terms of social, insti-

tutional, technological, and economic issues. How-

ever, this discussion does not pay enough attention to

the issues of quality design of the MOOC both in the

technological and pedagogical perspectives.

Prospects of MOOC learners, quality criteria in

MOOC design are presented in the paper (Yousef

et al., 2014). In the study (Shoufan, 2019) authors

tried to ﬁnd out what motivates students to give a pos-

itive or negative rate to an educational video. This

study can help not only students searching for educa-

tional videos but videos developers towards improved

content quality and learning outcomes.

Conole (Conole, 2016) presented the 7Cs (Con-

ceptualize, Capture, Communicate, Collaborate, Con-

sider, Combine, Consolidate) Learning design frame-

work, which can be used to develop pedagogically

based MOOCs. Daradoumis et al. (Daradoumis

et al., 2013), Gros and Garc

ıa-Pe

nalvo (Gros and

Garc

ıa-Pe

nalvo, 2016) analyzed the state of devel-

opment of MOOC, studied Open Educational Re-

sources (OER), providing strategic opportunities for

improving the quality of education. Romero and Ven-

tura (Romero and Ventura, 2017) presents a compre-

hensive overview of the data management applica-

tions that are used to analyze MOOCs. Periwal and

Rana (Periwal and Rana, 2017) presented 4 models

for dropout prophecy in MOOCs. After an empiri-

cal analysis and evaluation of these models, Periwal

and Rana (Periwal and Rana, 2017) concluded that

for imbalance MOOC class data the model created

by the naive Bayes technique is more appropriate.

Cook (Cook, 2017), Shahzad et al. (Shahzad et al.,

2020), Fidalgo-Blanco et al. (Fidalgo-Blanco et al.,

2016) suggested a methodology for modeling the au-

dience of learners for MOOC. Cook (Cook, 2017) in-

troduced the Open Learner Model. Hew and Che-

ung (Hew and Cheung, 2014) presented a review of

the literature focusing on the MOOCs use by instruc-

tors or students. They suggested reasons why stu-

dents sign up for MOOCs: (1) the desire to learn

about a new topic, (2) to extend current knowledge,

(3) for personal challenge, and (4) the desire to col-

lect completion certiﬁcates. Baanqud et al. (Baanqud

et al., 2020), Liyanagunawardena (Liyanagunawar-

dena, 2015), Kaplan and Haenlein (Kaplan and Haen-

lein, 2016), Gen

e et al. (Gen

e et al., 2014) pro-

vides a large overview of the methods and techniques

for assessing students who study courses through

the MOOC platform. Some other studies of the

MOOCs learners behavior, MOOC instructions, cur-

ricula described in the papers (Brali

c et al., 2015;

Wang and Chou, 2015; Long, 2017; Gentile et al.,

2020; Gunawardena and Premawardhena, 2020; Ata-

pattu and Falkner, 2018; Romadhon et al., 2020; Bor-

rego, 2019). The predictive analysis, economic as-

pects of MOOCs presented in the papers (Mubarak

et al., 2021; Ma and Lee, 2020; Epelboin, 2017).

This article is a continuation of the author’s stud-

ies presented in (CP4B, 2016; Seidametova, 2016;

Seidametova and Moskaleva, 2017; Seidametova,

2018) in which the technological, social, logistical

and ﬁnancial aspects of MOOCs were analyzed.

2 CLASSIFICATION AND

COMPARISON OF MOOCS

There is an institutional classiﬁcation of MOOC

(Conole, 2016). For our purposes, more useful is the

classiﬁcation based on the pedagogical approaches

and training functions of MOOC. Depending on the

pedagogical approaches, there are following main

types of MOOCs:

1. cMOOC (connectivist MOOCs) is associated with

a socially-constructivist pedagogical approach to

learning. cMOOC uses blogs, wikis, social me-

dia for searching knowledge. The main interac-

tions take place in the formats “learner-learner”

and “learner-teacher”. The MOOC as acronym

appeared in context of connectivism.

The main focus of the cMOOC is the accumu-

lation of knowledge, creativity and communica-

tion of participants. The Web 2.0 platform is

used. cMOOCs allow learners throw the Face-

book, websites, Google meetings, Zoom, Discord,

Telegram and etc. to share materials. information

with the groups The pedagogical approach used

in the cMOOC is ﬂexible and sensitive to the spe-

ciﬁc needs of the participants. It helps to ﬁnd like-

minded people and gives an opportunity to expand

the network of contacts. Examples of platforms

MOOCs Types and Course Development

561

that use the cMOOC approach are SoloLearn (42

million users), Duolingo (300 million users).

The aim of cMOOC is to improve the quality of

education through the strengthening of horizontal

links and the stimulation of joint cooperation in

groups of learners.

2. xMOOC (“MOOC as eXtension of something

else”) uses the behavioral principle of acquiring

knowledge, by repetition and testing of knowl-

edge. xMOOC contains lectures, quizzes to

test the mastery of theoretical material, forums

for communicating with the instructor and other

students of the course. This brings together

xMOOC with the format of the traditional aca-

demic courses. Usually, students must comply

with the deadlines for submitting completed as-

signments.

The content of the courses is focused on duplica-

tion of knowledge. The goal of xMOOC is ef-

fective delivering of content to a wider audience.

Three key components of xMOOCs are content,

evaluation and communication.

xMOOC uses its own technology platform. Three

main providers Coursera, edX, and Udacity use

xMOOCs.

The terms cMOOC and xMOOC were introduced

by Stephen Downes, one of the creators of the ﬁrst

cMOOC (Kaplan and Haenlein, 2016).

3. Quasi MOOC uses online training, offers online

courses, representing an online resource, for ex-

ample, such as open courses: Khan Academy or

MIT OpenCourseWare. Online quasi MOOCs are

developed by teachers that can be not certiﬁed.

Quasi MOOCs are shorter MOOCs for contents

and skills and do not require a semester course

structure.

The purpose of the quasi MOOC is to provide ac-

cess to collections of free learning of the mini-

lections in various disciplines and for different

age groups of students. Quasi MOOCs can be

content-based (xMOOCs), task-based, network-

based (cMOOCs).

4. hMOOC is the hybrid MOOC or MOOC 3.0.

This concept supports hybrid or ﬂipped classes

(blended learning), integrates and combines on-

line and face-to-face teaching/learning.

In addition to the listed MOOCs, there are also

SPOC (small private online course) (Seidametova,

2016), COOC (corporate open online course), BOOC

(big open online course), aMOOC (adaptive mas-

sively open online course), bMOOC (blended massive

open online course) (Kaplan and Haenlein, 2016),

sMOOC (semi-massive open online course) (Conole,

2016), etc. The terminology in this new ﬁeld is still

not well established.

The pedagogy of MOOCs depends on the follow-

ing requirements: a curriculum (lessons, exercises,

learning results), video and interpretations, forums (as

interfaces for learning), jobs, exams and projects. Ta-

ble 1 illustrates the differences between cMOOCs and

xMOOCs.

Table 1: Differences between cMOOCs and xMOOCs.

cMOOCs xMOOCs

Self-organized Teacher-based

Networked Centralized

Content: learner gener-

ated

Content: teacher-deﬁned

ﬂexible, distributed,

video lecture

short assignment, video

lecture

Self- and peer-

assessment, e-test

Quiz, e-test, peer-review,

certiﬁcate

Open networking com-

munication

Limited interaction

Communication outside

MOOC platform

Built in the MOOC plat-

form

3 LOGISTIC OF THE MOOCS

DEVELOPMENT AND

DEPLOYMENT

Based on the author’s experience acquired in the de-

velopment of the MOOCs, we present the logistics

chain of MOOCs development and deployment on the

ﬁgures 1, 2, 3. These presentations allow understand-

ing the scope of the preliminary training (planning),

as well as organization and management work.

The development of the MOOCs begin with a

preparatory stage, during which it is necessary to un-

derstand the domain area, identify the target audience,

determine the development tools, and calculate the

project parameters (cost, capacity, quality, and dura-

tion). At the end of this stage, a plan-project should be

prepared. Then the organizational stage begins – de-

signing the course, preparing the material, selecting

trainers, solving copyright problems, preparing video

materials, etc. All this is displayed in the production

plan. After preparing scenarios for lessons, videos,

tests, interviews, the penultimate stage of develop-

ment begins – the management stage. This stage im-

plies marketing, course assembly, approbation. The

last stage of development is the launch of the course.

At the stage of preliminary preparation of the

AET 2020 - Symposium on Advances in Educational Technology

562

Figure 1: The MOOC preproduction process.

MOOC it is necessary:

1. Identify the narrowed, desired learning outcomes

for students.

2. Provide a strategy for evaluating students, verify-

ing the mastery of knowledge in accordance with

speciﬁed learning outcomes.

3. Develop a sequence of tasks and actions that

will support the student’s actions in mastering the

learning objectives (knowledge, skills, activity):

• Availability of content that will support active

learning; model of activity / skills for students.

• Duration of the course, the course building

from basic knowledge to higher order of skills,

such as application, integration and analysis.

4. Ensure a balance between the presence of the

teacher / instructor, social and expert cooperation,

and the presence of cognitive challenges.

For the pedagogical design of each week (each

session) of the course, it is necessary to allocate:

planned results, content, activities, evaluation.

4 VIDEO CONTENT MATRIX BY

WEEKS OF STUDY

The matrix of video content for the weeks of study

should correspond to the expected learning outcomes.

It is a kind of template for displaying educational

material. Table 2 presents the video content matrix

of the MOOC “Unity Augmented Reality for Be-

ginners” (UnityAR4B) (see also ﬁgures 4, 5) pre-

pared in the framework of research work by grad-

uates of Applied Informatics major at the Crimean

State Engineering-Pedagogical University. The stu-

dents prepared 8 videos with duration of 3-5 minutes

each (the videos can be viewed on our YouTube chan-

nel CP4B, https://t.ly/c3b4). The language of these

lectures and videos is Russian.

We can make the following recommendations on

the variety of presentation forms of the video con-

tent. These recommendations are based on the ex-

perience of the videos production. Video content for

the MOOC can be represented by following video op-

tions:

• An introduction to the topic or subtopic with the

explaining teacher on the screen: the head or

MOOCs Types and Course Development

563

Figure 2: The MOOC production process.

1/3 of the upper part of body. This option usu-

ally uses to activate the previously studied mate-

rial. It contains background information (formu-

las, schemes, diagrams, etc.), presents the learn-

ing objectives of the topic.

• The optimal video length between three and six

minutes.

• Voice guidance of the video cast with the presen-

tation of the educational material. We can see on

the video slides of the presentation, screen cast,

annotations using the tablet or iPad, frames, pro-

gramming environment, etc.

• Video taken in a specially equipped room or in a

certain location – if it is acceptable, the instructor

can be placed in a different context for connection

with key concepts or with the professional com-

munity.

• Interviews – for example, it can be a short inter-

view with a regional representative, or an expert

on a given topic.

• The screencast format allows the instructor to in-

clude point slides, images, or motion (for exam-

ple, hand drawing on the board).

• Simulations can be used for illustrating course

concepts and engaging students, such videos can

be linked to an assignment or learning activity.

• Summarizing – the instructor / teacher summa-

rizes the topic and gives the guidelines for the next

topic, i.e. establishes a link between the topics.

5 TOOLS FOR VIDEO

PROCESSING

Designing video for learning purposes is something

like a conceptual challenge. Gunawardena and

Premawardhena (Gunawardena and Premawardhena,

2020), Atapattu and Falkner (Atapattu and Falkner,

AET 2020 - Symposium on Advances in Educational Technology

564

Figure 3: The MOOC postproduction process.

2018), Romadhon et al. (Romadhon et al., 2020)

show that videos used in a presentation mode foster

passive watching instead of reﬂective-learning activi-

ties.

To prepare the video content, it can be used one of

the video processing software:

• Edius (http://www.grassvalley.com/products/

subcat-editing software) – proprietary video

editing software for computer running Windows,

the latest version is Edius 9.10.

• Camtasia Studio / Camtasia for Mac (https://

www.techsmith.com/camtasia.html) – shareware

software for capturing video from the screen, al-

lows to record audio from a microphone, and al-

lows to place on the screen videos from a webcam.

• ScreenFlow (Mac) (http://www.telestream.net/

screenﬂow/overview.htm) – proprietary commer-

cial software for the macOS operating system,

Apple Inc. for screen casting and video editing.

• Apple iMovie is a video editing software applica-

tion for macOS, iOS devices.

6 POSSIBLE ROLES FOR

PARTICIPANTS OF THE MOOC

DEVELOPMENT TEAM

The MOOC involves many staff – the teaching team

that designed the course, the teaching team that led

the course, researchers, university staff, tutors.

To effectively design and develop a high qual-

ity MOOC, the development team needs the follow-

ing roles, representing domain experts, curriculum

designers, and technically skilled specialists. Based

on the experience of preparing the MOOC “Web-

framework Ruby on Rails for beginners” (RoR4B),

these roles can be described as follows:

• Head / expert on educational technologies – con-

ducts consultations and gives recommendations

on MOOC planning, an educational strategy, ad-

ministrative process, resources, educational poli-

cies.

• Instructor / teacher – allocates the appropriate ma-

terial for the course, designs the main activities

and evaluation, plans to the presentation of the

content, the rubric for expert evaluation.

• Copywriter – helps in choosing resources and

MOOCs Types and Course Development

565

Figure 4: The screenshot of the video 5 “Augmented Reality. Letters and words recognition” from play list of the q-MOOC

“Unity Augmented Reality for Beginners” (UnityAR4B).

Table 2: Quasi MOOC “Unity AR for beginners” video content matrix by weeks of study.

Lesson 1 Lesson 2 Lesson 3

Week 1 1.1 Introduction to Augmented

Reality

1.2 Installation of Unity. Unity

Interface. Understanding differ-

ent panels in Unity. Moving, ro-

tating and scaling. Objects in

Unity. Physics in Unity

1.3 Vuforia package. Importing

Vuforia inside Unity. Capturing

an Image. Creating a Vuforia

Database. Image Targets

Week 2 2.1 Creating a Canvas and

adding a Background image

2.2 The Recognition of the let-

ters and words

2.3 Projecting 3D Model on Im-

age Target. Customizing the let-

ters image target

Week 3 3.1 Designing UI buttons inside

the Canvas. Programming the UI

buttons. Programming Back and

Exit button inside the AR Scene

3.2 Building the app and testing

the output

3.3 Compiling AR app to An-

droid devices

• Assistant (TA) – helps in the design of resources,

the selection of materials, the preparation of writ-

ten questions, development and maintenance, for

example, in aspects that require special knowl-

edge of content. TA monitors the discussion fo-

rums of the MOOC and evaluation components

during the activity of this course.

• Video specialist – responsible for the production

of video materials, video. Video specialist edits,

mounts the original video, creates a video project,

and synchronizes the sound with the video image

and uploads the video to the MOOC platform, on

YouTube.

• The course’s producer (CP) – CP edits screen

capture components, organizes video in sections

(lessons) of lectures. CP adds meaningful ques-

tions to the video content / captured screen. CP

constructs a survey, homework or evaluation com-

ponents.

7 CONCLUSIONS

Nowadays MOOCs movements are one of the most

innovative initiatives within e-learning and distance

education that create new learning opportunities in

open and university education. However, there are

not consolidated approaches regarding the logistic of

MOOCs design and development.

Students who register for MOOC pursue differ-

AET 2020 - Symposium on Advances in Educational Technology

566

Figure 5: The fragment of the video “Architecture of the 4Stylish Application” from play list of the q-MOOC “Machine

Learning for beginners” (ML4B).

ent goals. Designing the MOOC as training course,

it is necessary to take into account all the wishes and

opportunities of the learner’s audience. The imple-

mentation of the MOOC described in the article, is

a typical MOOC development roadmap: recommen-

dations for content preparation, video content, auto-

matic evaluation, role-based speciﬁcations.

The roadmap is derived from the experience of de-

veloping MOOC in the discipline “Unity Augmented

Reality for beginners” (UnityAR4B) (CP4B, 2016).

In the future it is planned to develop statistical tools

for this MOOC, as well as to study personalization

issues that will take into account the desires and op-

portunities of students.

REFERENCES

Alario-Hoyos, C., P

erez-Sanagust

ın, M., Cormier, D., and

Delgado-Kloos, C. (2014). Proposal for a concep-

tual framework for educators to describe and design

MOOCs. Journal of Universal Computer Science,

20(1):6–23. http://www.jucs.org/jucs 20 1/proposal

for a conceptual.

Atapattu, T. and Falkner, K. (2018). Impact of Lecturer’s

Discourse for Students’ Video Engagement: Video

Learning Analytics Case Study of MOOCs. Journal

of Learning Analytics, 5(3):182–197. https://learning-

analytics.info/index.php/JLA/article/view/5748.

Baanqud, N. S., Al-Samarraie, H., Alzahrani, A. I., and Al-

farraj, O. (2020). Engagement in cloud-supported col-

laborative learning and student knowledge construc-

tion: a modeling study. International Journal of Edu-

cational Technology in Higher Education, 17(1):1–23.

Borrego,

A. (2019). The impact of MOOCs

on library and information science educa-

tion. Education for Information, 35(2):87–98.

https://content.iospress.com/articles/education-for-

information/eﬁ190269.

Brali

c, A.,

Cuku

c, M., and Jadri

c, M. (2015). Compar-

ing MOOCs in m-learning and e-learning settings. In

2015 38th International Convention on Information

and Communication Technology, Electronics and Mi-

croelectronics (MIPRO), pages 979–985.

Conole, G. (2016). MOOCs as disruptive tech-

nologies: strategies for enhancing the learner

experience and quality of MOOCs. Revista

de Educaci

on a Distancia (RED), 50(2):1–18.

https://www.um.es/ead/red/39/conole.pdf.

Cook, R. W. (2017). MOOClm: Learner Modelling for

MOOCs. Master’s thesis, University of Sydney.

http://hdl.handle.net/2123/17023.

CP4B (2016). Nedelia 1. Urok 1. Sistemy

schisleniia. Dvoichnaia sistema schisleniia.

https://www.youtube.com/watch?v=Ri0-sHRgGrk&

list=PLRz3zeDhGIhtkzw uhPD OK1QeYp1cZQe.

Daradoumis, T., Bassi, R., Xhafa, F., and Caball

e, S. (2013).

A Review on Massive E-Learning (MOOC) Design,

Delivery and Assessment. In 2013 Eighth Interna-

tional Conference on P2P, Parallel, Grid, Cloud and

Internet Computing, pages 208–213.

Epelboin, Y. (2017). Moocs: A viable business model? In

Jemni, M., Kinshuk, and Khribi, M. K., editors, Open

Education: from OERs to MOOCs, pages 241–259.

Springer Berlin Heidelberg, Berlin, Heidelberg.

MOOCs Types and Course Development

567

Fidalgo-Blanco,

A., Sein-Echaluce, M. L., and Garc

ıa-

nalvo, F. J. (2016). From massive access to coop-

eration: lessons learned and proven results of a hybrid

xMOOC/cMOOC pedagogical approach to MOOCs.

International Journal of Educational Technology in

Higher Education, 13(1):1–13.

Gen

e, O. B., N

nez, M. M., and Blanco, A. F. (2014). Gam-

iﬁcation in MOOC: Challenges, Opportunities and

Proposals for Advancing MOOC Model. In Proceed-

ings of the Second International Conference on Tech-

nological Ecosystems for Enhancing Multiculturality,

TEEM ’14, page 215–220, New York, NY, USA. As-

sociation for Computing Machinery.

Gentile, T. A. R., Reina, R., De Nito, E., Bizjak, D.,

and Canonico, P. (2020). E-learning design and en-

trepreneurship in three European universities. Inter-

national Journal of Entrepreneurial Behavior & Re-

search, 26(7):1547–1566.

Gros, B. and Garc

ıa-Pe

nalvo, F. J. (2016). Future trends

in the design strategies and technological affordances

of e-learning. In Spector, M. J., Lockee, B. B., and

Childress, M. D., editors, Learning, Design, and Tech-

nology: An International Compendium of Theory, Re-

search, Practice, and Policy, pages 1–23. Springer In-

ternational Publishing, Cham.

Gunawardena, C. N. and Premawardhena, N. C. (2020).

Online course design for student centered learn-

ing. http://192.248.16.117:8080/research/bitstream/

70130/5021/1/Online%20Course%20Design%

20for%20Student%20Centered%20Learning.pdf.

Hew, K. F. and Cheung, W. S. (2014). Students’ and instruc-

tors’ use of massive open online courses (MOOCs):

Motivations and challenges. Educational Research

Review, 12:45–58.

Kaplan, A. M. and Haenlein, M. (2016). Higher education

and the digital revolution: About MOOCs, SPOCs,

social media, and the Cookie Monster. Business Hori-

zons, 59(4):441–450.

Liyanagunawardena, T. R. (2015). Massive Open Online

Courses. Humanities, 4(1):35–41. https://www.mdpi.

com/2076-0787/4/1/35.

Long, Y. (2017). Explore the business model of MOOCs.

In Nah, F. F.-H. and Tan, C.-H., editors, HCI in Busi-

ness, Government and Organizations. Interacting with

Information Systems, pages 181–193, Cham. Springer

International Publishing.

Ma, L. and Lee, C. S. (2020). A motivational design ap-

proach to integrate moocs in traditional classrooms.

In Ishita, E., Pang, N. L. S., and Zhou, L., editors,

Digital Libraries at Times of Massive Societal Tran-

sition, pages 187–195, Cham. Springer International

Publishing.

Mubarak, A. A., Cao, H., and Ahmed, S. A. (2021). Pre-

dictive learning analytics using deep learning model

in moocs’ courses videos. Education and Information

Technologies, 26(1):371–392.

Periwal, N. and Rana, K. (2017). An empirical comparison

of models for dropout prophecy in MOOCs. In 2017

International Conference on Computing, Communica-

tion and Automation (ICCCA), pages 906–911.

Romadhon, M. I., Suprapto, Muhammad, O., and Qo-

mariyah, N. (2020). Instructional design learning:

A framework of a blended discovery-project model

in electronic engineering. In Proceedings of the

2020 11th International Conference on E-Education,

E-Business, E-Management, and E-Learning, IC4E

2020, page 1–4, New York, NY, USA. Association for

Computing Machinery.

Romero, C. and Ventura, S. (2017). Educational

data science in massive open online courses.

WIREs Data Mining and Knowledge Discovery,

7(1):e1187. https://wires.onlinelibrary.wiley.com/doi/

abs/10.1002/widm.1187.

Saltzman, G. M. (2014). The economics of moocs. In

Wechsler, H. S., editor, The NEA 2014 Almanac of

Higher Education, pages 19–29, Washington. Na-

tional Education Association, National Education As-

sociation. http://campus.albion.edu/gsaltzman/ﬁles/

2014/09/Economics of MOOCs-2014 Almanac of

Higher Education.pdf.

Saltzman, G. M. (2017). Economics of Massive Open On-

line Courses, Higher Education. In Shin, J. C. and

Teixeira, P., editors, Encyclopedia of International

Higher Education Systems and Institutions, pages 1–

4. Springer Netherlands, Dordrecht.

Seidametova, Z. (2016). MOOC course development: video

content matrix and role speciﬁcation. Information and

computer technologies in economics, education and

social domain, 1(11):5–16.

Seidametova, Z. (2018). Design and development of moocs.

CEUR Workshop Proceedings, 2104:462–471.

Seidametova, Z. and Moskaleva, Y. P. (2017). Logistics and

business models of MOOC and SPOC courses. Sci-

entiﬁc notes of the Crimean Engineering-Pedagogical

University, 3(57):60–65.

Shah, D. (2020a). By the numbers: MOOCs during the pan-

demic. https://www.classcentral.com/report/mooc-

stats-pandemic/.

Shah, D. (2020b). By the numbers: MOOCs in

2020. https://www.classcentral.com/report/mooc-

stats-2020/.

Shahzad, A., Hassan, R., Aremu, A. Y., Hussain, A., and

Lodhi, R. N. (2020). Effects of COVID-19 in E-

learning on higher education institution students: the

group comparison between male and female. Quality

& Quantity, pages 1–22.

Shoufan, A. (2019). What motivates university students

to like or dislike an educational online video? A

sentimental framework. Computers & Education,

134:132–144.

Wang, Y.-J. and Chou, C. (2015). A Study of the Eval-

uation Dimensions and Criteria for OpenCourseWare

Websites. Journal of Educational Media & Library

Sciences, 52(2):191–225.

Yousef, A. M. F., Chatti, M. A., Schroeder, U., and Wos-

nitza, M. (2014). What Drives a Successful MOOC?

An Empirical Examination of Criteria to Assure De-

sign Quality of MOOCs. In 2014 IEEE 14th Inter-

national Conference on Advanced Learning Technolo-

gies, pages 44–48.

AET 2020 - Symposium on Advances in Educational Technology

568